Small animal models play an irreplaceable role in the study of ocular diseases, but the need for structural information at different stages of a disease leads to time-consuming histology, inefficient use of animals, and large variability. Our long-term objective is to develop a high throughput testing facility that provides quantitative, non-invasive, high resolution, structural imaging of animal models of ophthalmic diseases. By high throughput we mean the acquisition of images and the extraction of desired information as efficiently and rapidly as possible, thereby maximizing the scientific yield of the facility. The facility will use a novel investigator-controlled animal alignment system that allows rapid selection of the imaged retinal areas together with ultra-high resolution spectral-domain OCT (optical coherence tomography) to provide 3D retinal images. To evaluate disease-induced damage and progression and to monitor treatment effects, the cell layers of the retina will be quantified using 3D segmentation of the OCT images. This project promises to significantly reduce the number of animals needed to achieve many research objectives. Collaborating scientists using small animal models for their research will provide valuable feedback to enhance the facility's productivity. The specific aims of the proposed research are to: 1. Design and build a novel animal alignment system together with a slit lamp biomicroscope based ultra-high resolution spectral-domain OCT and robust interchangeable optical probes for high throughput imaging of the anterior segment and retina of small animals. The animal alignment system that allows rapid selection of the imaging areas of interest. 2. Develop 3-D segmentation algorithms for (1) automatic segmentation of the RNFL of the retina and (2) automatic segmentation of the boundaries of retinal tumor. These algorithms will provide quantitative information (e.g., RNFL thickness maps and tumor volume) about the change that occurs at different stages of a disease. 3. Apply the system and algorithms to studying animal models of ocular diseases. We will first focus on three rodent models: (1) we will image changes in retinal structure in a rat glaucoma model, including changes of optic nerve and RNFL thickness at different stages of glaucoma damage;(2) We will quantitatively evaluate progression and treatment effect in a mouse model of retinoblastoma;(3) We will study the status and prognosis of a murine model of corneal transplant. PUBLIC HEALTH RELEVANCE: The proposed research will provide a powerful tool that will greatly accelerate the research on ocular diseases like glaucoma, retinoblastoma, and corneal transplant. It promises not only to reduce the number of animals required but also possible longitudinal studies that are currently impossible to conduct.